Literature DB >> 23691823

Hangar talk survey: using stories as a naturalistic method of informing threat and error management training.

Suzanne K Kearns1, Jennifer E Sutton.   

Abstract

OBJECTIVE: The current study developed an online hangar talk survey (HTS) to solicit narratives describing challenging scenarios that professional pilots encountered during the hours-building phase of their career.
BACKGROUND: The predicted pilot shortage will effectively reduce the minimum flying hours required for pilots to be hired at an airline, resulting in less opportunity to develop nontechnical skills naturalistically. To compensate, threat and error data from the hours-building phase of a pilot's career are required to inform training development. Pilots often share stories of such experiences, colloquially termed "hangar talk".
METHOD: The HTS gathered 132 narrative descriptions of general aviation (GA) events from pilots along with the event's impact and whether the pilots would react differently if the scenario were encountered again.
RESULTS: The distribution of threats reported by GA pilots was similar to that reported at the airline level. Logistic regression analysis revealed that decision-making errors were associated with recognition of the need to react differently in the future, and decision-making errors and proficiency errors were associated with greater perceived impact on skill development.
CONCLUSION: The current HTS solicited an array of data similar to the findings of airline-based threat and error observations. Pilots perceive decision-making and proficiency errors as impactful on skill development. APPLICATION: An HTS can be used to gather naturalistic threat and error data and to create a database of operational stories that can be used to develop nontechnical training based on narrative thought.

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Year:  2013        PMID: 23691823     DOI: 10.1177/0018720812452127

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  1 in total

Review 1.  Threat and error management for anesthesiologists: a predictive risk taxonomy.

Authors:  Keith J Ruskin; Marjorie P Stiegler; Kellie Park; Patrick Guffey; Viji Kurup; Thomas Chidester
Journal:  Curr Opin Anaesthesiol       Date:  2013-12       Impact factor: 2.706

  1 in total

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